An automated trading tool gives a user the ability to set up a program that can respond automatically to patterns in market activity, and in response, submit orders directly to an electronic exchange. The use of such trading tools is on the rise and for good reason. Sophisticated trading tools can intelligently sense market conditions and automatically respond—often much faster than a human. Until recently, such sophisticated trading tools were only available to a limited number of people. Now, in a marketplace where automated programs commonly trade against automated programs, in those circumstances, a manual-style trader may find it difficult to survive without some kind of automated assistance.
Automated trading tools are frequently used to hedge, which is a trading strategy made to reduce the risk of adverse price movements in a tradable object, by taking an offsetting position in the same or a related tradable object. For instance, a trader might execute a trade in one market (e.g., the “non-hedging” side), with the intention of quickly offsetting that position in another market (e.g., the “hedging” side). An automated trading tool is what most often performs at least the latter function—offsetting the position by quickly firing an order to the hedging side once the non-hedging order is matched. Hedging also includes taking an offsetting position in the same tradable object, such that the market represents both the hedging side and the non-hedging side.
A trader might use an automated trading tool in this way to trade a spread, which generally refers to the buying and/or selling of two or more tradable objects, the purpose of which is to capitalize on changes or movements in the relationships between the tradable objects. As used herein, the term “tradable object,” refers simply to anything that can be traded with a quantity and/or price. It includes, but is not limited to, all types of tradable events, goods, and financial products. For instance, stocks, options, bonds, futures, currency, and warrants, as well as funds, derivatives and collections of the foregoing, and all types of commodities, such as grains, energy, and metals may be considered tradable objects. A tradable object may be “real,” such as products that are listed by an exchange for trading, or “synthetic,” such as a combination of real products that is created by the user. A tradable object could actually be a combination of other tradable object, such as a class of tradable objects.
Here is an example to illustrate. Some traders trade one tradable object—e.g., a trader might trade the September corn contract. That is, the trader is offering to buy or willing to sell the September corn contract, depending on his or her trading strategy. Likewise, a trader might trade the December corn contract. Some traders, however, trade more than one tradable object at a time. For example, a trader might want to spread trade the September corn contract and the December corn contract. Buying the “September/December” spread refers to buying the September corn contract and selling the December corn contract. Selling the “September/December” spread refers to selling the September corn contract and buying the December corn contract. Spreading can also be done based on other relationships besides calendar months. One such example would be trading a 10-year note and a 5-year note. According to these examples given above, the spread has two legs. Legs refer to the portions of the trades associated with each individual tradable object, which is also referred to as an outright market. For example, the “September/December” corn calendar spread has two legs, the September corn market makes up a leg and the December corn market makes up the other leg.
Spreads can have more than two legs. For example, a well-known spread strategy called the butterfly involves buying a near month contract, selling two middle month contracts, and buying a far month contract. An example might be buying “1” March corn contract, selling “2” June corn contracts, and buying “1” December corn contract. The butterfly spread strategy in this example has three legs. The March corn market makes up a first leg, the June corn market makes up a second leg, and the December corn market makes up a third leg. There are many other types of well-known spread strategies, besides the butterfly, which have more than two legs.
A commercially available trading tool that facilitates the automatic trading of spreads is Autospreader™ from Trading Technologies International, Inc. of Chicago, Ill. Once the legs of the spread are chosen and the relationship between them are defined, a user can input a desired spread price and quantity, and the Autospreader™ will automatically work orders in the legs to achieve the desired spread (or attempt to achieve the spread). The Autospreader™ is currently an add-on tool available with X_TRADER® Pro™, which is a trading application also available from Trading Technologies International, Inc.
U.S. patent application Ser. No. 10/137,979, entitled, “System and Method for Performing Automatic Spread Trading,” filed on May 3, 2002, the contents of which are fully incorporated by reference herein, describes one such automated spread trading tool. An example is provided herein to illustrate how an automated spread trading tool like that described in the above incorporated application might work. While the example illustrates hedging in a related tradable object, the same concepts can be similarly applied to hedging in the same tradable object.
The market information given in FIG. 1 is used to illustrate the following example. In particular, FIG. 1 displays example order book information for two hypothetical tradable objects, referenced in the figure as product “1” and product “2.”Each of the tradable objects may be offered by one electronic exchange or separate electronic exchanges; it does not matter for this example. The bid quantity is shown in the left columns, the corresponding price—or some symbolic representation thereof—is shown in the center columns, and the ask quantity is shown in the right columns for each tradable object. While presenting the order book information in this manner makes it easier to illustrate the following example, the actual format of the order book information does not matter for this example.
The inside market for each tradable object includes the best bid price (or the highest bid) and the best ask price (or the lowest ask). The best bid price represents the highest price any buyer is willing to pay for a given tradable object at a given time, and the best ask price represents the lowest price any seller is willing to sell a given tradable object at a given time. The quantity available at the inside market and at other price levels is referred to as market depth. Referring to FIG. 1, at a current moment in time, the inside market for product “1” is bid at “295” and ask at “297.” The quantity available for product “1” at the inside market is “165” at the bid and “210” at the ask.
The inside market for product “2” is bid at “240” and ask at “242.” The quantity available for product “2” at the inside market is “230” at the bid and “150” at the ask. Other bid and ask quantities at various price levels are also shown.
To begin, a trader will typically input certain parameters that the trader wishes to achieve by the spread trading tool, such as a desired spread price and a desired spread quantity. Then, the spread trading tool will use a predefined relationship of the spread to determine what actions to take next. As an example, let us assume that the desired spread price is “55” and the desired spread quantity is “750,” although any price or quantity may be specified. In addition, let us assume that the trader wishes to sell the spread, which refers to selling “750” of product “1” and then, when that order is matched, the trader wishes to buy “750” of product “2.” It is understood that the trader could choose a different spread price and/or spread quantity, and also the trader could set up the spread in a number of different ways (e.g., buying the spread, which refers to buying product “1” and selling product “2,” etc.). Nonetheless, using the entered spread information, we will look at two different approaches generally taken by an automated spread trading tool.
The automated spread trading tool determines the price to sell “750” of product “1” by first determining the price would buy “750” of product “2.” According to one approach (referred to as the “first approach” in FIG. 1), the trading tool will simply look to the lowest ask price of “242” because that represents the best price for which product “2” may be bought by the trader. (Alternatively, if the hedge order was to sell in product “2,” the assumed price might be “242” because that represents the best price for which product “2” may be sold by the trader). Realizing that the best price to buy product “2” is “242,” the non-hedging order to sell product “1” is priced at “297” in an effort to achieve the desired spread price of “55,” (e.g., 55=297−242).
Unfortunately, there is not “750” available to buy at “242.” Therefore, what would really happen is that the quantity at the next best prices (e.g., “243,” “244,” etc) would be bought up until the hedge order of “750” is filled. As a result, according to this example, the hedge order would actually average a price of “243,” assuming that the market conditions did not change. The following relationship may be used to compute the average price at which “750” of product “2” could be bought:
                    (                  150          750                )            ⁢      242        +                  (                  350          750                )            ⁢      243        +                  (                  225          750                )            ⁢      244        +                  (                  25          750                )            ⁢      245        =  243Because the average fill price for the hedge order was higher than previously anticipated, the achieved spread price would be “56,” which is different from the desired spread price of “55.” Oftentimes, this result is undesired because it can amount to a significant loss of money.
According to another approach (referred to as the “second approach” according to FIG. 1), the automated spread trading tool will account for the market depth in product “2.” In doing so, the spread trading tool is computing a hedge order price based on a weighted average of prices. With this example, if the quantity needed was “750,” then the weighted average price may be computed by taking quantity from various prices starting from the best price, which results in a price of “243.” Realizing that the hedge order would actually be priced at “243,” the non-hedging order to sell product “1” is priced at “298” in an effort to achieve the desired spread price of “55,” (e.g., 55=298−243).
Unfortunately, in this instance, the nonhedging order is priced further off the market price in an effort to take into account the market depth. Because the non-hedging order is priced higher than market, it risks not being filled at all.
As automated trading tools become the norm in electronic trading, it is increasingly important to develop more intelligent tools to assist the trader in making the most desirable trades.